# Model Card for Model ID # Fin-Gemma-3s Fin-Gemma-3s is a fine-tuned model based on Google's Gemma 2B, specifically tailored for financial conversations and questions. This model is a significant step forward in promoting financial literacy. ## Model Details - **Model Name**: Fin-Gemma-3s - **Base Model**: Google Gemma 2B - **Fine-Tuned On**: A dataset that includes responses from ChatGPT-4.0 to financial conversations and questions. ## Purpose The primary goal of Fin-Gemma-3s is to enhance financial literacy by providing accurate and insightful responses to financial queries. This model is designed to assist users in understanding complex financial concepts and making informed decisions. ## Usage To use this model, you can load it using the Hugging Face `transformers` library: ```python from transformers import AutoModel, AutoTokenizer # Load the tokenizer and model tokenizer = AutoTokenizer.from_pretrained("hardiktiwari/fin-gemma-3s") model = AutoModel.from_pretrained("hardiktiwari/fin-gemma-3s") # Example usage inputs = tokenizer("What is the impact of inflation on savings?", return_tensors="pt") outputs = model(**inputs) ``` ## Model Details ### Model Description This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional] - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses ### Direct Use [More Information Needed] ### Downstream Use [optional] [More Information Needed] ### Out-of-Scope Use [More Information Needed] ## Bias, Risks, and Limitations [More Information Needed] ### Recommendations Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data [More Information Needed] ### Training Procedure #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed] #### Speeds, Sizes, Times [optional] [More Information Needed] ## Evaluation ### Testing Data, Factors & Metrics #### Testing Data [More Information Needed] #### Factors [More Information Needed] #### Metrics [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] [More Information Needed] ## Environmental Impact Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional] [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]